基于粒子群优化的电磁离合器模糊控制研究  

Research on Fuzzy Control of Electromagnetic Clutch Based on Particle Swarm Optimization

作　　者：吴晓刚[1] 王旭东[1] 余腾伟[1] 张宇[1] 

机构地区：[1]哈尔滨理工大学汽车电子驱动控制与系统集成教育部工程研究中心,哈尔滨150080

出　　处：《中国机械工程》2010年第9期1071-1077,共7页China Mechanical Engineering

基　　金：黑龙江省科技攻关项目(GB08A306);黑龙江省教育厅科学技术研究项目(11531z03)

摘　　要：针对车辆起步过程中应用传统模糊控制存在的精度不高、自适应能力有限等问题,提出了应用粒子群算法优化模糊控制器量化因子的方法。优化的量化因子随环境变化以及负载变化实时跟踪模糊控制器的参数变化,使得模糊控制器的鲁棒性和控制精度都得到了提高。仿真与实验结果表明,在车辆起步过程中,与传统的模糊控制算法相比基于粒子群优化的模糊控制算法能够在减小冲击度的同时有效减小滑摩功,具有较为理想的起步效果。Aiming at the problems such as lower precision and limited adaptive capability when the traditional fuzzy control is applied on a car during starts,a quantizing factor of fuzzy controller based on PSO was proposed,the optimal quantizing factor was changed to follow parameter changes of fuzzy controller as environmental changes and load changes,so the robustness and control accuracy were improved.The simulation and experimental result show the fuzzy control algorithm based on PSO compared with the traditional fuzzy control algorithm can effectively decrease the work of slipping,at the same time decrease the shock degree,and achieve at the ideal starting effect.

关 键 词：自动变速 电磁离合器 粒子群 模糊控制 

分 类 号：U463.211[机械工程—车辆工程]